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Latinos are heavily affected with childhood asthma. Little is known about epigenetic mechanisms of asthma in Latino youth. We conducted a meta-analysis of two epigenome-wide association studies (EWAS) of asthma, using DNA from white blood cells (WBCs) from 1,136 Latino children and youth aged 6 to 20 years. Genes near the top CpG sites in this EWAS were examined in a pathway enrichment analysis, and we then assessed whether our results replicated those from publicly available data from three independent EWAS conducted in non-Latino populations. We found that DNA methylation profiles differed between subjects with and without asthma. After adjustment for covariates and multiple testing, two CpGs were differentially methylated at a false discovery rate (FDR)-adjusted P CAMK1D (Calcium/Calmodulin Dependent Protein Kinase ID) and TIGIT (T Cell Immunoreceptor With Ig And ITIM Domains). Moreover, 25 genomic regions were differentially methylated between subjects with and without asthma, at Šidák-corrected P

BACKGROUND: Epigenetic signatures in the nasal epithelium, which is a primary interface with the environment and an accessible proxy for the bronchial epithelium, might provide insights into mechanisms of allergic disease. OBJECTIVE: We aimed to identify and interpret methylation signatures in nasal epithelial brushes associated with rhinitis and asthma. METHODS: Nasal epithelial brushes were obtained from 455 children at the 16 year follow-up of the Dutch PIAMA birth cohort study. Epigenome-wide association studies (EWAS) were performed on asthma, rhinitis and asthma and/or rhinitis (AsRh) using logistic regression, and top results were replicated in two independent cohorts of African American and Puerto Rican children. Significant CpG sites (CpGs) were related to environmental exposures (pets, active and passive smoking and molds) during secondary school, and correlated to gene expression by RNA-sequencing (n=244). RESULTS: The EWAS identified CpGs significantly associated with rhinitis (n=81) and AsRh (n=75), but not with asthma. We significantly replicated 62 /81 CpGs with rhinitis, and 60/75 with AsRh, as well as one CpG with asthma. Methylation of cg03565274 was negatively associated with AsRh, and positively associated with pets exposure during secondary school. DNA methylation signals associated with AsRh were mainly driven by specific IgE positive subjects. DNA methylation related to gene transcripts that were enriched for immune pathways, and expressed in immune and epithelial cells. Nasal CpGs performed well in predicting AsRh. CONCLUSIONS: We identified replicable DNA methylation profiles of asthma and rhinitis in nasal brushes. Pets exposure may affect nasal epithelial methylation in relation to asthma and rhinitis. CLINICAL IMPLICATIONS: Nasal DNA methylation profiles may serve as biomarker of asthma and rhinitis, and can be used across different populations to predict the presence of asthma and/or rhinitis in children.

Background Epigenetic mechanisms could alter the airway epithelial barrier and ultimately lead to atopic diseases such as asthma. We aimed to identify DNA methylation profiles that are associated with- and could accurately classify-atopy and atopic asthma in school-aged children. Methods We did a genome-wide study of DNA methylation in nasal epithelium and atopy or atopic asthma in 483 Puerto Rican children aged 9-20 years, recruited using multistage probability sampling. Atopy was defined as at least one positive IgE (>= 0.35 IU/mL) to common aeroallergens, and asthma was defined as a physician's diagnosis plus wheeze in the previous year. Significant (false discovery rate p Findings DNA methylation profiles were markedly different between children with (n=312) and without (n=171) atopy in the Puerto Rico discovery cohort, recruited from Feb 12, 2014, until May 8, 2017. After adjustment for covariates and multiple testing, we found 8664 differentially methylated CpGs by atopy, with false discovery rate-adjusted p values ranging from 9.58 x 10(-17) to 2.18 x 10(-22) for the top 30 CpGs. These CpGs were in or near genes relevant to epithelial barrier function, including CDHR3 and CDH26, and in other genes related to airway epithelial integrity and immune regulation, such as FBXL7, NTRK1, and SLC9A3. Moreover, 28 of the top 30 CpGs replicated in the same direction in both independent cohorts. Classification models of atopy based on nasal methylation performed well in the Puerto Rico cohort (area under the curve [AUC] 0.93-0.94 and accuracy 85-88%) and in both replication cohorts (AUC 0.74-0.92, accuracy 68-82%). The models also performed well for atopic asthma in the Puerto Rico cohort (AUC 0.95-1.00, accuracy 88%) and the replication cohorts (AUC 0.82-0.88, accuracy 86%). Interpretation We identified specific methylation profiles in airway epithelium that are associated with atopy and atopic asthma in children, and a nasal methylation panel that could classify children by atopy or atopic asthma. Our findings support the feasibility of using the nasal methylome for future clinical applications, such as predicting the development of asthma among wheezing infants. Copyright (C) 2018 Elsevier Ltd. All rights reserved.

Total IgE is a therapeutic target in patients with allergic diseases. DNA methylation in white blood cells (WBCs) was associated with total IgE levels in an epigenome-wide association study of white subjects. Whether DNA methylation of eosinophils explains these findings is insufficiently understood.We tested for association between genome-wide DNA methylation in WBCs and total IgE levels in 2 studies of Hispanic children: the Puerto Rico Genetics of Asthma and Lifestyle Study (PR-GOAL; n = 306) and the Genes-environments and Admixture in Latino Americans (GALA II) study (n = 573). Whole-genome methylation of DNA from WBCs was measured by using the Illumina Infinium HumanMethylation450 BeadChip. Total IgE levels were measured by using the UniCAP 100 system. In PR-GOAL WBC types (ie, neutrophils, eosinophils, basophils, lymphocytes, and monocytes) in peripheral blood were measured by using Coulter Counter techniques. In the GALA II study WBC types were imputed. Multivariable linear regression was used for the analysis of DNA methylation and total IgE levels, which was first conducted separately for each cohort, and then results from the 2 cohorts were combined in a meta-analysis.CpG sites in multiple genes, including novel findings and results previously reported in white subjects, were significantly associated with total IgE levels. However, adjustment for WBC types resulted in markedly fewer significant sites. Top findings from this adjusted meta-analysis were in the genes ZFPM1 (P = 1.5 × 10In an epigenome-wide association study adjusted for WBC types (including eosinophils), methylation changes in genes enriched in pathways relevant to asthma and immune responses were associated with total IgE levels among Hispanic children.

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450 K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ˜480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of two types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450 K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of eight normalization methods for 450 K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus β-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450 K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.